Lane Offset Survey for One-Lane Horizontal Curvatures Using Binocular Stereo Vision Measurement System

Liu, Lexuan

doi:10.1061/(asce)su.1943-5428.0000370

Cited by 4 publications

(1 citation statement)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When combined, UAVs and CNNs can quickly detect, classify, and locate objects in images. (1)(2)(3) Owing to these advantages, various studies have been conducted in areas such as flood mapping, (4) agriculture, (5)(6)(7)(8)(9) the environment, (10) traffic, (11)(12)(13)(14)(15) structure management, (16)(17)(18)(19)(20) archaeology, (21) and disaster management (22,23) using drones and CNNs.…”

Section: Introductionmentioning

confidence: 99%

Positioning Errors of Objects Measured by Convolution Neural Network in Unmanned Aerial Vehicle Images

Kang¹,

Kim²,

Yun³

et al. 2022

Sensors and Materials

View full text Add to dashboard Cite

The conversion of unmanned aerial vehicles (UAVs, also called drones) and convolution neural network (CNN) facilitates the location of objects in real time using their sensors. In photogrammetry, the positional accuracy of objects is directly affected by the use of technology. It is necessary to improve the accuracy of object positioning to increase the utilization of drones and CNNs. In this study, the error factors that impede accuracy, such as the global navigation satellite system (GNSS) error of the UAV, camera distortion error, and camera posture error, were analyzed to improve the accuracy of object positioning. The effect of each error was also analyzed. The study was conducted in stages, such as establishing a method for the positioning of objects, specifying errors, and analyzing the amount and effect of error elements. The magnitude of the positioning errors was found by comparing it with accurate values measured by GNSS. Furthermore, the correlation of the errors with the factors that impeded accuracy was analyzed. Consequently, the effect of each error factor on the overall error was identified. These results can play an important role in improving positioning accuracy and developing UAV and CNN technologies employing sensors in the future.

show abstract